The NaijaVoices Dataset: Cultivating Large-Scale, High-Quality, Culturally-Rich Speech Data for African Languages
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Abstract (arXiv)
The development of high-performing, robust, and reliable speech technologies depends on large, high-quality datasets. However, African languages -- including our focus, Igbo, Hausa, and Yoruba -- remain under-represented due to insufficient data. Popular voice-enabled technologies do not support any of the 2000+ African languages, limiting accessibility for circa one billion people. While previous dataset efforts exist for the target languages, they lack the scale and diversity needed for robust speech models. To bridge this gap, we introduce the NaijaVoices dataset, a 1,800-hour speech-text dataset with 5,000+ speakers. We outline our unique data collection approach, analyze its acoustic diversity, and demonstrate its impact through finetuning experiments on automatic speech recognition, averagely achieving 75.86% (Whisper), 52.06% (MMS), and 42.33% (XLSR) WER improvements. These results highlight NaijaVoices' potential to advance multilingual speech processing for African languages.
Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). Builds on 24 of its 36 references that are in the map. First posted on arXiv 26 May 2025.
Builds on
24 of 36 references.
References · 24
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- 2022A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translationcited by 97
12 more
- 2024BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of datacited by 75
- 2023The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AIcited by 73
- 2020Masakhane -- Machine Translation For Africacited by 48
- 2024IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languagescited by 39
- 2022BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpuscited by 31
- 2024IndicVoices-R: Unlocking a Massive Multilingual Multi-speaker Speech Corpus for Scaling Indian TTScited by 15
- 2023Multilingual self-supervised speech representations improve the speech recognition of low-resource African languages with codeswitchingcited by 11
- 2024Voices Unheard: NLP Resources and Models for Yor`ub'a Regional Dialectscited by 11
- 2022Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Taskscited by 9
- 2022YFACC: A Yor`ub'a speech-image dataset for cross-lingual keyword localisation through visual groundingcited by 8
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- 2022A Proposal to Study "Is High Quality Data All We Need?"cited by 2
Built on by
Citing papers per year: 2025: 2; 2026: 5.
7 papers.
- 2025Cost Analysis of Human-corrected Transcription for Predominately Oral Languagescited by 3
- 2025Dealing with the Hard Facts of Low-Resource African NLPcited by 2
- 2026WorldSpeech: A Multilingual Speech Corpus from Around the Worldcited by 0
- 2026Sometin Beta Pass Notin: Improving Multilingual ASR for Nigerian Languages via Knowledge Distillationcited by 0
- 2026WAXAL-NET: Finetuned Edge ASR Across 19 African Languagescited by 0
- 2026From Speech to Text Corpora: Evaluating ASR-Based Data Acquisition for Low-Resource Fongbe and Hausacited by 0
- 2026AfriSwitch: A Benchmark for In-the-Wild African Code-Switched Speech Recognitioncited by 0
- 2026AfriSwitch: A Benchmark for In-the-Wild African Code-Switched Speech Recognition26 Aug 2026
- 2026From Speech to Text Corpora: Evaluating ASR-Based Data Acquisition for Low-Resource Fongbe and Hausa20 Jun 2026
- 2026WAXAL-NET: Finetuned Edge ASR Across 19 African Languages1 Jun 2026
- 2026Sometin Beta Pass Notin: Improving Multilingual ASR for Nigerian Languages via Knowledge Distillation18 May 2026
- 2026WorldSpeech: A Multilingual Speech Corpus from Around the World9 May 2026
- 2025Dealing with the Hard Facts of Low-Resource African NLP23 Nov 2025
- 2025Cost Analysis of Human-corrected Transcription for Predominately Oral Languages14 Oct 2025